python 3.x - numpy.dot() gives TypeError: can't multiply sequence by non-int of type 'float' -


i have begun learning machine learning using python. have written following class gives error:

typeerror: can't multiply sequence non-int of type 'float'

class perceptron(object):     def __init__(self, eta=0.01, n_iter=10):         self.eta = eta                          # learning rate         self.n_iter = n_iter                    # number of iteration on training dataset      def fit(self, x, y):         self.w_ = np.zeros(1 + x.shape[1])      # initialize weights 0                                                # x = {array-like} : shape[no_of_samples, no_of_features]         self.errors_ = []                       # no errors in beginning of computation         _ in range(self.n_iter):             errors = 0             xi, target in zip(x, y):                 update = self.eta * (target - self.predict(xi))                 self.w_[1:] += update * xi                 self.w_[0] += update                 errors += int(update != 0.0)             self.errors_.append(errors)          return self      def net_input(self, x):         return np.dot(x, self.w_[1:]) + self.w_[0]      def predict(self, x):         return np.where(self.net_input(x) >= 0.0, 1, -1)

i getting error in net_input() method @ np.dot(). using following dataset : https://raw.githubusercontent.com/uiuc-cse/data-fa14/gh-pages/data/iris.csv

following changes help. 

def fit(self, x, y):     ...     xi, target in zip(x, y):         update = self.eta * (target - self.predict(xi.reshape(1, x.shape[1]))         ...  # here if want implement perceptron, use matmul not dot product def net_input(self, x):     return np.matmul(x, self.w_[1:]) + self.w_[0]

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